Effect of Divalent Metal Ion on the Structure, Stability and Function of Klebsiella pneumoniae Nicotinate-Nucleotide Adenylyltransferase: Empirical and Computational Studies.
Olamide JejeReabetswe MaakeRuan van DeventerVeruschka EsauEmmanuel Amarachi IwuchukwuVanessa MeyerThandeka KhozaIkechukwu AchilonuPublished in: International journal of molecular sciences (2021)
The continuous threat of drug-resistant Klebsiella pneumoniae justifies identifying novel targets and developing effective antibacterial agents. A potential target is nicotinate nucleotide adenylyltransferase (NNAT), an indispensable enzyme in the biosynthesis of the cell-dependent metabolite, NAD + . NNAT catalyses the adenylation of nicotinamide/nicotinate mononucleotide (NMN/NaMN), using ATP to form nicotinamide/nicotinate adenine dinucleotide (NAD + /NaAD). In addition, it employs divalent cations for co-substrate binding and catalysis and has a preference for different divalent cations. Here, the biophysical structure of NNAT from K. pneumoniae (KpNNAT) and the impact of divalent cations on its activity, conformational stability and substrate-binding are described using experimental and computational approaches. The experimental study was executed using an enzyme-coupled assay, far-UV circular dichroism, extrinsic fluorescence spectroscopy, and thermal shift assays, alongside homology modelling, molecular docking, and molecular dynamic simulation. The structure of KpNNAT revealed a predominately α-helical secondary structure content and a binding site that is partially hydrophobic. Its substrates ATP and NMN share the same binding pocket with similar affinity and exhibit an energetically favourable binding. KpNNAT showed maximum activity and minimal conformational changes with Mg 2+ as a cofactor compared to Zn 2+ , Cu 2+ and Ni 2+ . Overall, ATP binding affects KpNNAT dynamics, and the dynamics of ATP binding depend on the presence and type of divalent cation. The data obtained from this study would serve as a basis for further evaluation towards designing structure-based inhibitors with therapeutic potential.
Keyphrases
- klebsiella pneumoniae
- multidrug resistant
- drug resistant
- molecular docking
- ionic liquid
- single molecule
- dna binding
- escherichia coli
- molecular dynamics simulations
- binding protein
- high throughput
- acinetobacter baumannii
- single cell
- molecular dynamics
- machine learning
- transcription factor
- big data
- pseudomonas aeruginosa
- cell therapy
- aqueous solution
- artificial intelligence